Biology subjects

Cagiada, M.

Publications and source records attributed to Cagiada, M..

21 records · Page 2Linked to original sources

bioRxiv2022

A multiplexed assay of human glucokinase reveals thousands of potential disease variants with both decreased and increased activity

Glucokinase (GCK) regulates insulin secretion to maintain appropriate blood glucose levels. Sequence variants can alter GCK activity to cause hyperinsulinemic hypoglycemia (HH) or hyperglycemia associated with GCK-maturity-onset diabetes of the young (GCK-MODY), collectively affecting up to 10 million people worldwide. Patients with GCK-MODY are frequently misdiagnosed and treated unnecessarily. Genetic testing can prevent this but is hampered by the challenge of interpreting novel missense variants. Here we exploited a multiplexed yeast complementation assay to measure both hyper- and hypoactive GCK variation, capturing 97% of all possible missense and nonsense variants. Activity scores correlated with in vitro catalytic efficiency, fasting glucose levels in carriers of GCK variants and with evolutionary conservation. Hypoactive variants were concentrated at buried positions, near the active site, and at a region of known importance for GCK conformational dynamics. Some hyperactive variants shifted the conformational equilibrium towards the active state through a relative destabilization of the inactive conformation. Our comprehensive assessment of GCK variant activity promises to facilitate variant interpretation and diagnosis, expand our mechanistic understanding of hyperactive variants, and inform development of therapeutics targeting GCK.

genetics↗

bioRxiv2021

Predicting and interpreting large scale mutagenesis data using analyses of protein stability and conservation

Understanding and predicting the functional consequences of single amino acid is central in many areas of protein science. Here we collected and analysed experimental measurements of effects of >150,000 variants in 29 proteins. We used biophysical calculations to predict changes in stability for each variant, and assessed them in light of sequence conservation. We find that the sequence analyses give more accurate prediction of variant effects than predictions of stability, and that about half of the variants that show loss of function do so due to stability effects. We construct a machine learning model to predict variant effects from protein structure and sequence alignments, and show how the two sources of information are able to support one another. Together our results show how one can leverage large-scale experimental assessments of variant effects to gain deeper and general insights into the mechanisms that cause loss of function.

biophysics↗

bioRxiv2020

Understanding the origins of loss of protein function by analyzing the effects of thousands of variants on activity and abundance

Understanding and predicting how amino acid substitutions affect proteins is key to our basic understanding of protein function and evolution. Amino acid changes may affect protein function in a number of ways including direct perturbations of activity or indirect effects on protein folding and stability. We have analysed 6749 experimentally determined variant effects from multiplexed assays on abundance and activity in two proteins (NUDT15 and PTEN) to quantify these effects, and find that a third of the variants cause loss of function, and about half of loss-of-function variants also have low cellular abundance. We analyse the structural and mechanistic origins of loss of function, and use the experimental data to find residues important for enzymatic activity. We performed computational analyses of protein stability and evolutionary conservation and show how we may predict positions where variants cause loss of activity or abundance. In this way, our results link thermodynamic stability and evolutionary conservation to experimental studies of different properties of protein fitness landscapes.

biophysics↗